| The actual application scenarios of robots are complex and diverse.According to different task requirements,they often need to work in a mixed indoor and outdoor environment.The traditional single positioning method is difficult to meet the requirements of seamless positioning.Therefore,this paper studies the integrated navigation and positioning of robots based on multiple positioning techniques and uses data fusion filtering algorithms to improve the positioning performance of the system.Aiming at the problem that the fusion algorithm in the application process is not strong enough to adapt to the posit ioning mode jump switching and the radio ranging base station cannot be determined in advance,corresponding solutions are proposed to achieve the purpose of improving the seamless positioning accuracy of the robot indoor and outdoor.Firstly,considering that satellite navigation signals are sensitive to the environment and cannot provide positioning services indoors,a combined positioning structure based on UWB as a supplement to traditional GNSS/IMU integrated navigation is established.The state equation of the system is established based on the error model of the inertial navigation system,and the measurement equation is established taking into account the observation information of satellite navigation and ultra-wideband positioning respectively.Both of them constitute the mathematical model of the combined positioning algorithm,and then it is verified by simulation.Secondly,a seamless positioning adaptive filtering algorithm based on degree of observability analysis-interactive multi model is proposed to solve the problem of allocation and selection of different information sources in seamless positioning and the switching and jump of integrated system caused by environmental changes.The improved degree of observability analysis method is used to evaluate the performance of the current system filter,and then the effect of Markov transition probability matrix on the performance of the algorithm in the interactive multi-model is analyzed.By modifying the transition probability based on the degree of observability,the algorithm can effectively adjust the filtering mode and the weight of observation information according to the jump of positioning mode,which improves the adaptive ability of the algorithm.Then,to solve the problem of UWB base station deployment in indoor and outdoor areas where satellite navigation signals are missing,an optimal deployment algorithm based on geometric dilution of precision-maximum base station convex hull is proposed.Using the geometric dilution of precision as the evaluation index,the objective function and constraint conditions of the problem solving are defined,and the necessity and solution of finding the convex hull of the bottom base station are analyzed.Then,the results of base station layout in a specific area are verified by simulation.The simulation results show that the algorithm can accurately find the layout scheme that meets the minimum condition of the accuracy factor,and has higher calculation efficiency.Finally,a robot integrated navigtaion test platform is built to verify the positioning accuracy and algorithm,the system design plan is explained,and the function of each module is tested.A robot positioning experiment is carried out,and the effectiveness of the algorithm is verified through the experiment.The experimental results show that the integrated system can meet the needs of the robot's indoor and outdoor seamless positioning. |
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